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[FLINK-17795][example] Add MatrixVectorMul example
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...ples-streaming/src/main/java/org/apache/flink/streaming/examples/gpu/MatrixVectorMul.java
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you under the Apache License, Version 2.0 (the | ||
| * "License"); you may not use this file except in compliance | ||
| * with the License. You may obtain a copy of the License at | ||
| * | ||
| * https://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| package org.apache.flink.streaming.examples.gpu; | ||
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| import org.apache.flink.api.common.externalresource.ExternalResourceInfo; | ||
| import org.apache.flink.api.common.functions.RichMapFunction; | ||
| import org.apache.flink.api.common.serialization.SimpleStringEncoder; | ||
| import org.apache.flink.api.java.utils.ParameterTool; | ||
| import org.apache.flink.configuration.Configuration; | ||
| import org.apache.flink.core.fs.Path; | ||
| import org.apache.flink.streaming.api.datastream.DataStream; | ||
| import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; | ||
| import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink; | ||
| import org.apache.flink.streaming.api.functions.source.RichSourceFunction; | ||
| import org.apache.flink.util.Preconditions; | ||
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| import jcuda.Pointer; | ||
| import jcuda.Sizeof; | ||
| import jcuda.jcublas.JCublas; | ||
| import jcuda.runtime.JCuda; | ||
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| import java.util.ArrayList; | ||
| import java.util.List; | ||
| import java.util.Optional; | ||
| import java.util.Set; | ||
| import java.util.UUID; | ||
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| /** | ||
| * Implements the matrix-vector multiplication program that shows how to use GPU resources in Flink. | ||
| * | ||
| * <p>The input is a vector stream from a {@link RandomVectorSource}, which will generate random vectors with specified | ||
| * dimension. The data size of the vector stream could be specified by user. Each vector will be multiplied with a random | ||
| * dimension * dimension matrix in {@link Multiplier} and the result would be emitted to output. | ||
| * | ||
| * <p>Usage: MatrixVectorMul [--output <path>] [--dimension <dimension> --data-size <data_size>] | ||
| * | ||
| * <p>If no parameters are provided, the program is run with default vector dimension 10 and data size 100. | ||
| * | ||
| * <p>This example shows how to: | ||
| * <ul> | ||
| * <li>leverage external resource in operators, | ||
| * <li>accelerate complex calculation with GPU resources. | ||
| * </ul> | ||
| * | ||
| * <p>Notice that you need to add JCuda natives libraries in your Flink distribution by the following steps: | ||
| * <ul> | ||
| * <li>download the JCuda native libraries bundle for your CUDA version from https://www.jcuda.org/downloads/ | ||
| * <li>copy the native libraries jcuda-natives and jcublas-natives for your CUDA version, operating system and architecture | ||
| * to the "lib/" folder of your Flink distribution | ||
| * </ul> | ||
| */ | ||
| public class MatrixVectorMul { | ||
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| private static final int DEFAULT_DIM = 10; | ||
| private static final int DEFAULT_DATA_SIZE = 100; | ||
| private static final String DEFAULT_RESOURCE_NAME = "gpu"; | ||
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| public static void main(String[] args) throws Exception { | ||
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| // Checking input parameters | ||
| final ParameterTool params = ParameterTool.fromArgs(args); | ||
| System.out.println("Usage: MatrixVectorMul [--output <path>] [--dimension <dimension> --data-size <data_size>] [--resource-name <resource_name>]"); | ||
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| // Set up the execution environment | ||
| final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); | ||
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| // Make parameters available in the web interface | ||
| env.getConfig().setGlobalJobParameters(params); | ||
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| final int dimension = params.getInt("dimension", DEFAULT_DIM); | ||
| final int dataSize = params.getInt("data-size", DEFAULT_DATA_SIZE); | ||
| final String resourceName = params.get("resource-name", DEFAULT_RESOURCE_NAME); | ||
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| DataStream<List<Float>> result = env.addSource(new RandomVectorSource(dimension, dataSize)) | ||
| .map(new Multiplier(dimension, resourceName)); | ||
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| // Emit result | ||
| if (params.has("output")) { | ||
| result.addSink(StreamingFileSink.forRowFormat(new Path(params.get("output")), | ||
| new SimpleStringEncoder<List<Float>>()).build()); | ||
| } else { | ||
| System.out.println("Printing result to stdout. Use --output to specify output path."); | ||
| result.print(); | ||
| } | ||
| // Execute program | ||
| env.execute("Matrix-Vector Multiplication"); | ||
| } | ||
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| // ************************************************************************* | ||
| // USER FUNCTIONS | ||
| // ************************************************************************* | ||
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| /** | ||
| * Random vector source which generates random vectors with specified dimension and total data size. | ||
| */ | ||
| private static final class RandomVectorSource extends RichSourceFunction<List<Float>> { | ||
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| private transient volatile boolean running; | ||
| private final int dimension; | ||
| private final int dataSize; | ||
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| RandomVectorSource(int dimension, int dataSize) { | ||
| this.dimension = dimension; | ||
| this.dataSize = dataSize; | ||
| } | ||
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| @Override | ||
| public void open(Configuration parameters) { | ||
| running = true; | ||
| } | ||
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| @Override | ||
| public void run(SourceContext<List<Float>> ctx) { | ||
| int count = 0; | ||
| while (running && count < dataSize) { | ||
| List<Float> randomRecord = new ArrayList<>(); | ||
| for (int i = 0; i < dimension; ++i) { | ||
| randomRecord.add((float) Math.random()); | ||
| } | ||
| ctx.collect(randomRecord); | ||
| count += 1; | ||
| } | ||
| } | ||
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| @Override | ||
| public void cancel() { | ||
| running = false; | ||
| } | ||
| } | ||
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| /** | ||
| * Matrix-Vector multiplier using CUBLAS library. | ||
| */ | ||
| private static final class Multiplier extends RichMapFunction<List<Float>, List<Float>> { | ||
| private final int dimension; | ||
| private final String resourceName; | ||
| private Pointer matrixPointer; | ||
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| Multiplier(int dimension, String resourceName) { | ||
| this.dimension = dimension; | ||
| this.resourceName = resourceName; | ||
| } | ||
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| @Override | ||
| public void open(Configuration parameters) { | ||
| // When multiple instances of this class and JCuda exist in different class loaders, then we will get UnsatisfiedLinkError. | ||
| // To avoid that, we need to temporarily override the java.io.tmpdir, where the JCuda store its native library, with a random path. | ||
| // For more details please refer to https://issues.apache.org/jira/browse/FLINK-5408 and the discussion in https://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/Classloader-and-removal-of-native-libraries-td14808.html | ||
| final String originTempDir = System.getProperty("java.io.tmpdir"); | ||
| final String newTempDir = originTempDir + "/jcuda-" + UUID.randomUUID(); | ||
| System.setProperty("java.io.tmpdir", newTempDir); | ||
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| final Set<ExternalResourceInfo> externalResourceInfos = getRuntimeContext().getExternalResourceInfos(resourceName); | ||
| Preconditions.checkState(!externalResourceInfos.isEmpty(), "The MatrixVectorMul needs at least one GPU device while finding 0 GPU."); | ||
| final Optional<String> firstIndexOptional = externalResourceInfos.iterator().next().getProperty("index"); | ||
| Preconditions.checkState(firstIndexOptional.isPresent()); | ||
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| matrixPointer = new Pointer(); | ||
| final float[] matrix = new float[dimension * dimension]; | ||
| // Initialize a random matrix | ||
| for (int i = 0; i < dimension * dimension; ++i) { | ||
| matrix[i] = (float) Math.random(); | ||
| } | ||
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| // Set the CUDA device | ||
| JCuda.cudaSetDevice(Integer.parseInt(firstIndexOptional.get())); | ||
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| // Initialize JCublas | ||
| JCublas.cublasInit(); | ||
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| // Allocate device memory for the matrix | ||
| JCublas.cublasAlloc(dimension * dimension, Sizeof.FLOAT, matrixPointer); | ||
| JCublas.cublasSetVector(dimension * dimension, Sizeof.FLOAT, Pointer.to(matrix), 1, matrixPointer, 1); | ||
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| // Change the java.io.tmpdir back to its original value. | ||
| System.setProperty("java.io.tmpdir", originTempDir); | ||
| } | ||
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| @Override | ||
| public List<Float> map(List<Float> value) { | ||
| final float[] input = new float[dimension]; | ||
| final float[] output = new float[dimension]; | ||
| final Pointer inputPointer = new Pointer(); | ||
| final Pointer outputPointer = new Pointer(); | ||
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| // Fill the input and output vector | ||
| for (int i = 0; i < dimension; i++) { | ||
| input[i] = value.get(i); | ||
| output[i] = 0; | ||
| } | ||
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| // Allocate device memory for the input and output | ||
| JCublas.cublasAlloc(dimension, Sizeof.FLOAT, inputPointer); | ||
| JCublas.cublasAlloc(dimension, Sizeof.FLOAT, outputPointer); | ||
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| // Initialize the device matrices | ||
| JCublas.cublasSetVector(dimension, Sizeof.FLOAT, Pointer.to(input), 1, inputPointer, 1); | ||
| JCublas.cublasSetVector(dimension, Sizeof.FLOAT, Pointer.to(output), 1, outputPointer, 1); | ||
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| // Performs operation using JCublas | ||
| JCublas.cublasSgemv('n', dimension, dimension, 1.0f, | ||
| matrixPointer, dimension, inputPointer, 1, 0.0f, outputPointer, 1); | ||
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| // Read the result back | ||
| JCublas.cublasGetVector(dimension, Sizeof.FLOAT, outputPointer, 1, Pointer.to(output), 1); | ||
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| // Memory clean up | ||
| JCublas.cublasFree(inputPointer); | ||
| JCublas.cublasFree(outputPointer); | ||
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| List<Float> outputList = new ArrayList<>(); | ||
| for (int i = 0; i < dimension; ++i) { | ||
| outputList.add(output[i]); | ||
| } | ||
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| return outputList; | ||
| } | ||
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| @Override | ||
| public void close() { | ||
| // Memory clean up | ||
| JCublas.cublasFree(matrixPointer); | ||
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| // Shutdown cublas | ||
| JCublas.cublasShutdown(); | ||
| } | ||
| } | ||
| } |